{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MinPy (MXNet NumPy)\n",
    "\n",
    "*\"Everybody loves NumPy.\"*\n",
    "\n",
    "In this tutorial, we present MinPy -- a NumPy-like package based on MXNet. NumPy is a well-known python package widely used in scientific computing, statistics and machine learning. It supports a wide range of tensor operators and is very friendly to machine learning beginners. Here, we will walk with you through a simple example of *logistic regression* using NumPy. After that we will illustrate how MinPy utilizes GPUs to speed up your machine learning algorithm with few (or no) changes in your original NumPy code. We hope by following this direction, we could solve the ultimate trade-off that every machine learning tools are facing with: *how to achieve both efficiency and flexibility?*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# A bit of setup, just ignore this cell.\n",
    "from __future__ import absolute_import\n",
    "from __future__ import print_function\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# For auto-reloading external modules.\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "%matplotlib inline\n",
    "# Set default size of plots.\n",
    "plt.rcParams['figure.figsize'] = (8.0, 6.0)\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Before start:* MinPy is still a work in progress, so you may encounter problems when playing with it. You could always try *Kernel->Restart & Clear Output* and go through the tutorial again."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multinomial Logistic Regression using NumPy\n",
    "\n",
    "Logistic regression is a supervised machine learning algorithm that is commonly used in classification. The *supervised* word here means each data sample (represented by a float vector) is *labeled*. We have provided some util functions to fetch some generated data for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shapes: data (10000, 500), label (10000, 5)\n",
      "#samples: 10000\n",
      "#features: 500\n",
      "#classes: 5\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import numpy.random as random\n",
    "import time\n",
    "from util import get_data, plot_data\n",
    "\n",
    "# Initialize training data.\n",
    "data, label = get_data()\n",
    "num_samples = data.shape[0]\n",
    "num_features = data.shape[1]\n",
    "num_classes = label.shape[1]\n",
    "\n",
    "print('Shapes: data {}, label {}'.format(data.shape, label.shape))\n",
    "print('#samples: {}'.format(num_samples))\n",
    "print('#features: {}'.format(num_features))\n",
    "print('#classes: {}'.format(num_classes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our example, the training data contains 10000 samples. Each sample has 500 features, so the training samples could be represented by a 10000 x 500 matrix. Our goal is to classify each sample into 5 classes. Therefore, each sample comes with a label which is encoded in *one-of-many* format. For example, say sample 0 is of class 1, then the corresponding label vector for sample 0 will be `[0, 1, 0, 0, 0]`. Therefore, label could be represented by a 10000 x 5 matrix as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data matrix:\n",
      "[[ 0.32734496  0.38202421  0.88363333 ...,  0.56855788  0.77482872\n",
      "   0.78661045]\n",
      " [ 0.30944119  0.31369851  0.7323332  ...,  0.52735346  0.54504115\n",
      "   0.86898225]\n",
      " [ 0.37802308  0.43419765  0.66645294 ...,  0.64980071  0.55614532\n",
      "   0.76352769]\n",
      " ..., \n",
      " [ 0.23139488  0.46588139  0.54704782 ...,  0.8856756   0.07421766\n",
      "   0.61662582]\n",
      " [ 0.00828138  0.17924487  0.53160273 ...,  1.05838437  0.1968327\n",
      "   0.63039901]\n",
      " [ 0.05748305  0.27938298  0.46694946 ...,  0.82950457  0.06558127\n",
      "   0.6286073 ]]\n",
      "\n",
      "Label matrix:\n",
      "[[ 1.  0.  0.  0.  0.]\n",
      " [ 1.  0.  0.  0.  0.]\n",
      " [ 1.  0.  0.  0.  0.]\n",
      " ..., \n",
      " [ 0.  0.  0.  0.  1.]\n",
      " [ 0.  0.  0.  0.  1.]\n",
      " [ 0.  0.  0.  0.  1.]]\n"
     ]
    }
   ],
   "source": [
    "print('Data matrix:')\n",
    "print(data)\n",
    "print()\n",
    "print('Label matrix:')\n",
    "print(label)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We provide a function `plot_data` for you to visualize what the data looks like. It projects each 500-D samples onto their first two dimensions, so each sample is a point in the figure. We distinguish samples of different classes using different colors. Although this is a very simple example, the idea behind is similar to more complicated examples you will encounter in the following tutorials. For example, if this is an *Optical Character Recognition (OCR)* task (like the MNIST example we are going to talk about), you could think about the blue points are the samples of digit 0 and red points are digit 1. Then our goal is to correctly classify some *unknown* samples (test data) into the most likely classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ground truth:\n"
     ]
    },
    {
     "data": {
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8EXjsMar9PnKEMtjdbqoJB4C/+isS8c5O1fJ/9llaGHzhC3TuQ4dUF3pFBW3T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43u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\nvuM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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb27c9dfb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize what the ground truth data looks like.\n",
    "print('Ground truth:')\n",
    "plot_data(data, label)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model we are using here is called *Multinomial Logistic Regression*, or called *Softmax Regression*. Original logistic regression could only deal with binary classes (either 0 or 1) while multinomial logistic regression allows you to classify samples into multiple classes. The model contains a weight matrix `w` that projects from feature space to class space (so its dimension is $\\#feature \\times \\#class$). It first calculate the probability of each class given the samples:\n",
    "$$p(y^{(i)}=j \\mid x^{(i)};w)= \\frac{\\exp(w_j^Tx^{(i)})}{\\sum_k\\exp(w_k^Tx^{(i)})}.$$\n",
    "Try implement the following `predict` function that corresponds to the above math equation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Predict the class using logistic regression.\n",
    "def predict(w, x):\n",
    "    #===========================================================#\n",
    "    #                    Your code starts here                  #\n",
    "    #===========================================================#\n",
    "    # Please try compute the estimated probability of each sample.\n",
    "    a = np.exp(np.dot(x, w))\n",
    "    a_sum = np.sum(a, axis=1, keepdims=True)\n",
    "    prob = a / a_sum\n",
    "    #===========================================================#\n",
    "    #                    Your code ends here                    #\n",
    "    #===========================================================#\n",
    "    return prob"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could then use the above `predict` function to see what a random guess may look like. We first initialize the `weight` matrix using random numbers. Then feed the predict result into the `plot_data` function for visualization. You could see that, the random guess is completely different than the correct labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4cKAHPvtsFl55RUF2diSKiozo0qUW8fH5uHAhFeXl/sjPP4W77pqLY8f2Y/v2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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb2566d84d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initialize training weight.\n",
    "weight = random.randn(num_features, num_classes)\n",
    "\n",
    "# Visualize the initial guess.\n",
    "plot_data(data, predict(weight, data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Multinomial logistic regression then tries to minimize the *cross entropy* between the `predict` class probability and the correct probability. More specifically, it tries to minimize the following equation:\n",
    "$$J(w)=-\\frac{1}{m}\\left[\\sum_{i=1}^{m}\\sum_{j=1}^{k}1\\{y^{(i)}=j\\}\\log (p(y^{(i)}=j \\mid x^{(i)};w))\\right],$$\n",
    "where $m$ is the number of samples, $1\\{\\dots\\}$ is the indicator function which equals to 1 if the condition holds, otherwise equals to 0.\n",
    "\n",
    "Try implement the loss calculation in the following code. Note that our label (the correct probability) has already been transformed into *one-of-many* form, so the indicator function here is simply an element-wise multiplication of the label matrix and the logarithmic probability.\n",
    "\n",
    "To minimize this function, we use a method called **batch gradient descent**. It first calculates the gradient of the weight matrix as follows:\n",
    "$$\\nabla_{w}J(w)=-\\frac{1}{m}\\sum_{i=1}^{m}\\left[x^{(i)}(1\\{y^{(i)}=j\\}-p(y^{(i)}=j \\mid x^{(i)};w))\\right],$$\n",
    "then update the current model along the gradient direction:\n",
    "$$w\\leftarrow w - \\alpha \\nabla_{w}J(w).$$\n",
    "We have implemented the gradient computation and the weight update for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Using gradient descent to fit the correct classes.\n",
    "def train(w, x, loops):\n",
    "    for i in range(loops):\n",
    "        prob = predict(w, x)\n",
    "        #===========================================================#\n",
    "        #                    Your code starts here                  #\n",
    "        #===========================================================#\n",
    "        # Please try compute the current loss value.\n",
    "        loss = -np.sum(label * np.log(prob)) / num_samples\n",
    "        #===========================================================#\n",
    "        #                    Your code ends here                    #\n",
    "        #===========================================================#\n",
    "        if i % 10 == 0:\n",
    "            print('Iter {}, training loss {}'.format(i, loss))\n",
    "        # Calculate gradient of weight.\n",
    "        dy = prob - label\n",
    "        dw = np.dot(data.T, dy) / num_samples\n",
    "        # Update.\n",
    "        w -= 0.1 * dw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you have finished the above codes, you could now try to optimize it for 100 iterations. You should see the loss value dropping."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter 0, training loss 18.5933411618\n",
      "Iter 10, training loss 3.84047748176\n",
      "Iter 20, training loss 0.597952040726\n",
      "Iter 30, training loss 0.170459936203\n",
      "Iter 40, training loss 0.0889255625059\n",
      "Iter 50, training loss 0.0579375950023\n",
      "Iter 60, training loss 0.0421541291543\n",
      "Iter 70, training loss 0.0327540525306\n",
      "Iter 80, training loss 0.0265842613616\n",
      "Iter 90, training loss 0.0222565260358\n",
      "Training time: 2.99150300026s\n"
     ]
    }
   ],
   "source": [
    "# Now training it for 100 iterations.\n",
    "start_time = time.time()\n",
    "train(weight, data, 100)\n",
    "print('Training time: {}s'.format(time.time() - start_time))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now you could visualize the prediction with trained model again. It should now be very close to what the ground truth is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NYhXv3y8iuGaNbNPWJuILIpqHD8v7z38e/uzPYOVK6O0FlQ7wzDN2LB1gyRLJ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\nIveIZg57JFMVefFi2uci9+8t/Ly2gIrqatIGTWzbJlL739J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XK3LHZolhXlrugvUWiSAm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+6DoiJJoc3nkyRS51GhC5YdzYqLuyGVM0WmdPXqeRXsglXPgqVYryeDGqy0lpOQgN3j4T5RpGjp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\nAwDQUf8DY3cH59JHdHYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb2567d4a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the prediction after training. It should show similar image as the ground truth.\n",
    "plot_data(data, predict(weight, data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multinomial Logistic Regression using MinPy (MXNet NumPy)\n",
    "\n",
    "### Utilize GPU computation with little (or no) NumPy syntax change\n",
    "\n",
    "You could see even with such a tiny example, 100 iterations take around 9 seconds. In real world, there are billions of samples and much more features and classes. How to efficiently train such a model? One solution is to use GPU. Our tool, MinPy allows you to use GPU to speed up the algorithm and in the meantime, keep the neat NumPy syntax you just went through."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# All you need to do is replace the NumPy namespace with MinPy's.\n",
    "import minpy.numpy as np\n",
    "import minpy.numpy.random as random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter 0, training loss [ 20.35612297]\n",
      "Iter 10, training loss [ 2.90887713]\n",
      "Iter 20, training loss [ 0.4465476]\n",
      "Iter 30, training loss [ 0.15010837]\n",
      "Iter 40, training loss [ 0.08212418]\n",
      "Iter 50, training loss [ 0.05462361]\n",
      "Iter 60, training loss [ 0.04021417]\n",
      "Iter 70, training loss [ 0.03148827]\n",
      "Iter 80, training loss [ 0.02569447]\n",
      "Iter 90, training loss [ 0.02159448]\n",
      "Training time: 6.42448186874s\n"
     ]
    }
   ],
   "source": [
    "# Initialize weight matrix (again).\n",
    "weight = random.randn(num_features, num_classes)\n",
    "\n",
    "# Now call the same training function.\n",
    "# Since the namespace is redefined, it will automatically run on GPU.\n",
    "start_time = time.time()\n",
    "train(weight, data, 100)\n",
    " # You should observe a significant speed up (around 3x) to the previous training time.\n",
    "print('Training time: {}s'.format(time.time() - start_time))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Automatic gradient calculation\n",
    "\n",
    "Compute gradient is tedious especially for complex neural networks you will encounter in the following tutorials. Minpy is able to compute the gradient automatically given arbitrary loss function. Please implement the following loss function (or paste it from your previous codes). The `grad_and_loss` function takes your defined `train_loss` function and then returns a function which will calculate both the loss value and the gradient of weight. The gradient could then be directly used to update the model weight."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Quiz:** Try modify the loss function by adding an L2-regularization. The new loss function is as follows:\n",
    "$$J'(w)=J(w)+\\sum_{i}w_i^2.$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter 0, training loss [ 17.82495117]\n",
      "Iter 10, training loss [ 2.68323684]\n",
      "Iter 20, training loss [ 0.37757167]\n",
      "Iter 30, training loss [ 0.14777139]\n",
      "Iter 40, training loss [ 0.08515061]\n",
      "Iter 50, training loss [ 0.05801885]\n",
      "Iter 60, training loss [ 0.0433203]\n",
      "Iter 70, training loss [ 0.03424589]\n",
      "Iter 80, training loss [ 0.02814375]\n",
      "Iter 90, training loss [ 0.02378545]\n",
      "Training time: 6.82868885994s\n"
     ]
    }
   ],
   "source": [
    "from minpy.core import grad_and_loss\n",
    "\n",
    "# Initialize weight matrix (again).\n",
    "weight = random.randn(num_features, num_classes)\n",
    "\n",
    "# Using gradient descent to fit the correct classes.\n",
    "def train_loss(w, x):\n",
    "    #===========================================================#\n",
    "    #                    Your code starts here                  #\n",
    "    #===========================================================#\n",
    "    prob = predict(w, x)\n",
    "    loss = -np.sum(label * np.log(prob)) / num_samples\n",
    "    #===========================================================#\n",
    "    #                    Your code ends here                    #\n",
    "    #===========================================================#\n",
    "    return loss\n",
    "\n",
    "# Calculate gradient function automatically.\n",
    "grad_function = grad_and_loss(train_loss)\n",
    "\n",
    "# Now training it for 100 iterations.\n",
    "start_time = time.time()\n",
    "for i in range(100):\n",
    "    dw, loss = grad_function(weight, data)\n",
    "    if i % 10 == 0:\n",
    "        print('Iter {}, training loss {}'.format(i, loss))\n",
    "    weight -= 0.1 * dw\n",
    "print('Training time: {}s'.format(time.time() - start_time))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9eZH7Ucdck5JCRUYG31yzhudGRmZkyO8+c4Znh4Y4MDJCVVYWwch1do+NcTSy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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb256437750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the result.\n",
    "# ATTENTION: When calling an external package implemented by NumPy, you need to explicitly convert MinPy's array to NumPy's array.\n",
    "plot_data(data, predict(weight, data).asnumpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Graceful fallback when GPU operators are missing\n",
    "\n",
    "NumPy is a giant library with hundreds of operators. Our supported GPU operators are only a subset of them, so it is inevitable that you want to try some functions that are currently missing on GPU side. To solve this problem, MinPy gracefully adopts the NumPy implementation once the operator is missing on GPU side, and handles the memory copies among GPU and CPU for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mI0822 01:09:21 6018 minpy.array:_synchronize_data:488]\u001b[0m Copy from mxnet array to numpy array Node#140403929199728\n",
      "\u001b[32mI0822 01:09:21 6018 minpy.array:_synchronize_data:493]\u001b[0m Copy from numpy array to mxnet array Node#140403929199344\n"
     ]
    }
   ],
   "source": [
    "# First turn on the logging to know what happens under the hood.\n",
    "import logging\n",
    "logging.getLogger('minpy.array').setLevel(logging.DEBUG)\n",
    "\n",
    "x = np.zeros((10, 20))\n",
    "\n",
    "# `cosh` is currently missing in MXNet's GPU implementation.\n",
    "# So it will fallback to use NumPy's CPU implementation,\n",
    "# but you don't need to worry about the memory copy from GPU -> CPU\n",
    "y = np.cosh(x)\n",
    "\n",
    "# `log` has GPU implementation, so it will copy the array from CPU -> GPU.\n",
    "# Once again, you don't need to worry about it. It is transparent.\n",
    "z = np.log(y)\n",
    "\n",
    "# Turn off the logging.\n",
    "logging.getLogger('minpy.array').setLevel(logging.WARN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use predefined MXNet symbol as one operator\n",
    "\n",
    "Now we solve the problem of missing GPU operators. What if we want to use some efficient special operators for neural network that only have GPU implementation? For example, convolution is very slow in numpy's implementation, while NVIDIA provides very efficient CUDA implementation. Hence, MinPy allows you to directly use MXNet's symbol as one operator, and you could mix MXNet's declarative programming with Minpy's imperative programming in one piece of code. The following example replaces the computation of:\n",
    "$$p(y^{(i)}=j \\mid x^{(i)};w)= \\frac{\\exp(w_j^Tx^{(i)})}{\\sum_j\\exp(w_j^Tx^{(i)})}$$\n",
    " with a predefined `SoftmaxOutput` symbol."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Quiz: ** After you have gone through the next tutorial about MNIST OCR task. You could try replace the `np.dot` function with the `sym.FullyConnected` symbol. Remember, you could combine multiple symbols into one operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter 0, training loss [ 15.58731556]\n",
      "Iter 10, training loss [ 0.84335393]\n",
      "Iter 20, training loss [ 0.22376448]\n",
      "Iter 30, training loss [ 0.11309522]\n",
      "Iter 40, training loss [ 0.07235434]\n",
      "Iter 50, training loss [ 0.0519943]\n",
      "Iter 60, training loss [ 0.04000816]\n",
      "Iter 70, training loss [ 0.03220009]\n",
      "Iter 80, training loss [ 0.02675243]\n",
      "Iter 90, training loss [ 0.0227588]\n",
      "Training time: 6.19591403008s\n"
     ]
    }
   ],
   "source": [
    "import mxnet\n",
    "import mxnet.symbol as sym\n",
    "from minpy.core import Function\n",
    "\n",
    "# Define softmax symbol (this part will be covered in the later tutorial).\n",
    "x_shape = (num_samples, num_classes)\n",
    "label_shape = (num_samples,)\n",
    "softmax_symbol = sym.SoftmaxOutput(data=sym.Variable('x'), name='softmax', grad_scale=1.0/num_samples)\n",
    "\n",
    "# Convert MXNet symbol into a callable function (with corresponding gradient function).\n",
    "softmax = Function(softmax_symbol, {'x': x_shape, 'softmax_label': label_shape})\n",
    "\n",
    "# Make `softmax_label`. MXNet's softmax operator does not use one-of-many label format.\n",
    "softmax_label = np.argmax(label, axis=1)\n",
    "\n",
    "# Redefine loss function using softmax as one operator.\n",
    "def train_loss(w, x):\n",
    "    y = np.dot(x, w)\n",
    "    prob = softmax(x=y, softmax_label=softmax_label)\n",
    "    loss = -np.sum(label * np.log(prob)) / num_samples\n",
    "    return loss\n",
    "\n",
    "# Initialize weight matrix (again).\n",
    "weight = random.randn(num_features, num_classes)\n",
    "\n",
    "# Calculate gradient function automatically.\n",
    "grad_function = grad_and_loss(train_loss)\n",
    "\n",
    "# Now training it for 100 iterations.\n",
    "start_time = time.time()\n",
    "for i in range(100):\n",
    "    dw, loss = grad_function(weight, data)\n",
    "    if i % 10 == 0:\n",
    "        print('Iter {}, training loss {}'.format(i, loss))\n",
    "    weight -= 0.1 * dw\n",
    "print('Training time: {}s'.format(time.time() - start_time))"
   ]
  }
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